PhD Position Hybrid Safe Learning for Inter-Connected Systems (AI)

TL;DR

PhD Researcher (AI/ML): Developing a robust hybrid learning framework combining online and offline learning paradigms for interconnected systems with an accent on model plasticity and performance guarantees. Focus on designing algorithms for 6G and Edge AI platforms to prevent catastrophic forgetting and handle non-IID streaming data.

Location: Must relocate to the Netherlands (Delft)

Salary: €3,059 – €3,881 gross per month

Company

hirify.global is a top international university combining science, engineering, and design to address global challenges in energy, climate, mobility, and digital society.

What you will do

• Develop a robust hybrid learning framework at the nexus of online and offline learning.
• Create algorithms capable of utilizing existing training data and real-time streaming data.
• Implement mechanisms to achieve model plasticity while avoiding catastrophic forgetting.
• Establish interpretable and robust accuracy and performance guarantees for developed algorithms.
• Apply research to 6G and Edge AI platforms in collaboration with industry partners and domain experts.

Requirements

• Master’s degree in Computer Science, Machine Learning, Operations Research, Applied Mathematics, or related fields.
• Strong mathematical foundations in optimization techniques (e.g., LP, CVX) and first-order methods for ML.
• Hands-on experience in data analysis using Python and proficiency with Deep Learning libraries.
• Excellent command of written and spoken English.
• Willingness to relocate to the Netherlands.

Culture & Benefits

• 4-year employment period with a structured progress assessment.
• Salary increases annually from €3,059 to €3,881 gross per month.
• 8% holiday allowance and an 8.3% end-of-year bonus.
• Customizable compensation package and discounts on health insurance.
• Relocation support via the Coming to Delft Service and a Dual Career Programme for partners.
• Access to the hirify.global Graduate School's research environment and Doctoral Education Programme.

Hiring process

• Application requires a detailed CV, motivation letter (max 1 page), and BSc/MSc transcripts.
• Final stages include a knowledge security risk assessment.